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Session overview

Session overview. Monetary Unit Sampling (MUS) advantages limitations, and relevance to substantive test of details Steps in MUS. Learning objectives.

stacey-morris
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Session overview

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  1. Session overview • Monetary Unit Sampling (MUS) • advantages • limitations, and • relevance to substantive test of details • Steps in MUS Session 7.1

  2. Learning objectives • At the end of the session, you would be able to apply MUS to substantive test of details, to the extent, that the steps are applied correctly, keeping in mind, the advantages and limitations of MUS. Session 7.1

  3. Monetary Unit Sampling • ‘MUS is a method of sampling in which the sampling unit is an individual dollar and not an invoice or any other physical unit’. • MUS helps in arriving conclusions on physical units in monetary terms. Session 7.1

  4. Sample Selection Procedure • Work out cumulative total for each item. • Divide the cumulative total by the number of items to be selected to arrive at sampling interval. • In case of cell selection,form cells such that width of each cell is same as sampling interval and pick one number from each cell. Select item in which cumulative total is equal to number. • In case of systematic selection, select a number randomly, which is less than sampling interval. Add sampling interval to the first number/previous number to arrive at the other numbers and select items in which cumulative total is equal to the numbers. Session 7.1

  5. Advantages of MUS • Forecast of errors in monetary term • Items bigger than sampling interval will be selected • Weight given for high value items • Audit can be started without knowledge of population size. Session 7.1

  6. Disadvantages of MUS • Zero value items will be left out • Becomes very conservative if too many errors exist are found out in audit. • Not very suitable for understatement • Difficult to use with manually maintained accounts Session 7.1

  7. Steps in MUS • Make planning decisions • Select sample for substantive test of details • Project sample results Session 7.1

  8. Determining Sample Size • Set Upper Error Limit (equal to materiality) • Subtract estimated Most Likely Error • Subtract Precision Gap Widening • Basic Precision: BP = UEL-MLE-PGW • Locate Basic Precision factor • Average Sampling interval (ASI) = BP/BP factor • Deduct high value and key value items from population for representative population • Sample size = representative population/ASI Session 7.1

  9. Evaluating Sample Results • Calculate percentage of tainting for each items • Add all taintings for Net Tainting Percentage(NTP) • MLE = NTP * Average Sampling Interval (ASI) • Total MLE = MLE + error in high value & key items • Find out PGW factor from the statistical table for each error • Tainting adjusted PGW factor=Tainting percentage*PGW factor • Total tainting adjusted PGW factor for overstatement and understatement separately • PGW = sum of tainting adjusted PGW factors * ASI • UEL(overstatement) = MLE + BP + PGW • UEL(understatement)= MLE - BP - PGW Session 7.1

  10. Quiz Questions • Sample size is 75 for a population of 1000 for assurance of 95%. If assurance is increased to 99%, sample size would (increase/decrease) • Auditor expects an error of Rs.1000,000 in accounts receivable account. This is called Upper Error Limit (True/False) • Representative population divided by sampling interval would Session 7.1

  11. THANK YOU Session 7.1

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